This work presents the application of a new tool, Obiwan, which uses image simulations to determine the selection function of a galaxy redshift survey and calculate three-dimensional (3D) clustering statistics. Obiwan relies on a forward model of the process by which images of the night sky are transformed into a 3D large-scale structure catalogue, and offers several advantages over more traditional map-based techniques - such as operating on individual exposures and adopting a maximum likelihood approach. The photometric pipeline automatically detects and models galaxies and then generates a catalogue of such galaxies with detailed information for each one of them, including their location, redshift, and so on. Systematic biases in the imaging data are therefore imparted into the catalogues and must be accounted for in any scientific analysis of their information content. Obiwan simulates this process for samples selected from the Legacy Surveys imaging data. This imaging data will be used to select target samples for the next-generation Dark Energy Spectroscopic Instrument (DESI) experiment. Here, we apply Obiwan to a portion of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey emission-line galaxies (ELGs). Systematic biases in the data are clearly identified and removed. We compare the 3D clustering results to those obtained by the map-based approach applied to the complete eBOSS Data Release 16 (DR16) sample. We find the results are consistent, thereby validating the eBOSS DR16 ELG catalogues, which is used to obtain cosmological results.

The Dark Energy Spectroscopic Instrument Legacy Surveys, a combination of three ground-based imaging surveys, have mapped 16,000 deg2 in three optical bands (g, r, and z) to a depth 1-2 mag deeper than the Sloan Digital Sky Survey. Our work addresses one of the major challenges of wide-field imaging surveys conducted at ground-based observatories: the varying depth that results from varying observing conditions at Earth-bound sites. To mitigate these effects, the Legacy Surveys (the Dark Energy Camera Legacy Survey, or DECaLS; the Mayall z-band Legacy Survey, or MzLS; and the Beiijing-Arizona Sky Survey, or BASS) employed a unique strategy to dynamically adjust the exposure times as rapidly as possible in response to the changing observing conditions. We present the tiling and observing strategies used by the first two of these surveys. We demonstrate that the tiling and dynamic observing strategies jointly result in a more uniform-depth survey that has higher efficiency for a given total observing time compared with the traditional approach of using fixed exposure times.